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Volume 14, Issue 2
Orthogonality Sampling Method for Identifying Small Anomalies in Real-World Microwave Imaging

Chi Young Ahn, Seongje Chae, Sangwoo Kang, Kwang-Jae Lee, Won-Kwang Park & Seong-Ho Son

East Asian J. Appl. Math., 14 (2024), pp. 293-313.

Published online: 2024-04

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  • Abstract

In this paper, the application of the orthogonality sampling method (OSM) to the real-world microwave imaging for identifying location of small anomalies is addressed. In order to show the feasibility and limitation of the OSM, we theoretically prove that the indicator function can be represented in terms of an infinite series of Bessel functions of integer order and the transmitting and receiving signal antenna configurations. This is based on the application of the Born approximation and the reciprocity of the incident fields. Throughout real-data experiments, it was shown that the OSM works well for identifying single anomaly under the specific location of transmitter while further improvement is needed for identification of multiple anomalies. To improve the imaging performance, we consider traditional indicator function with multiple sources and design a new indicator function with multiple sources weighted by the incident field. Theoretical results are contained to demonstrate the improvement.

  • AMS Subject Headings

78A46

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COPYRIGHT: © Global Science Press

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@Article{EAJAM-14-293, author = {Ahn , Chi YoungChae , SeongjeKang , SangwooLee , Kwang-JaePark , Won-Kwang and Son , Seong-Ho}, title = {Orthogonality Sampling Method for Identifying Small Anomalies in Real-World Microwave Imaging}, journal = {East Asian Journal on Applied Mathematics}, year = {2024}, volume = {14}, number = {2}, pages = {293--313}, abstract = {

In this paper, the application of the orthogonality sampling method (OSM) to the real-world microwave imaging for identifying location of small anomalies is addressed. In order to show the feasibility and limitation of the OSM, we theoretically prove that the indicator function can be represented in terms of an infinite series of Bessel functions of integer order and the transmitting and receiving signal antenna configurations. This is based on the application of the Born approximation and the reciprocity of the incident fields. Throughout real-data experiments, it was shown that the OSM works well for identifying single anomaly under the specific location of transmitter while further improvement is needed for identification of multiple anomalies. To improve the imaging performance, we consider traditional indicator function with multiple sources and design a new indicator function with multiple sources weighted by the incident field. Theoretical results are contained to demonstrate the improvement.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.2022-318.170723}, url = {http://global-sci.org/intro/article_detail/eajam/23064.html} }
TY - JOUR T1 - Orthogonality Sampling Method for Identifying Small Anomalies in Real-World Microwave Imaging AU - Ahn , Chi Young AU - Chae , Seongje AU - Kang , Sangwoo AU - Lee , Kwang-Jae AU - Park , Won-Kwang AU - Son , Seong-Ho JO - East Asian Journal on Applied Mathematics VL - 2 SP - 293 EP - 313 PY - 2024 DA - 2024/04 SN - 14 DO - http://doi.org/10.4208/eajam.2022-318.170723 UR - https://global-sci.org/intro/article_detail/eajam/23064.html KW - Orthogonality sampling method, microwave imaging, infinite series of Bessel functions, real-data experiment. AB -

In this paper, the application of the orthogonality sampling method (OSM) to the real-world microwave imaging for identifying location of small anomalies is addressed. In order to show the feasibility and limitation of the OSM, we theoretically prove that the indicator function can be represented in terms of an infinite series of Bessel functions of integer order and the transmitting and receiving signal antenna configurations. This is based on the application of the Born approximation and the reciprocity of the incident fields. Throughout real-data experiments, it was shown that the OSM works well for identifying single anomaly under the specific location of transmitter while further improvement is needed for identification of multiple anomalies. To improve the imaging performance, we consider traditional indicator function with multiple sources and design a new indicator function with multiple sources weighted by the incident field. Theoretical results are contained to demonstrate the improvement.

Chi Young Ahn, Seongje Chae, Sangwoo Kang, Kwang-Jae Lee, Won-Kwang Park & Seong-Ho Son. (2024). Orthogonality Sampling Method for Identifying Small Anomalies in Real-World Microwave Imaging. East Asian Journal on Applied Mathematics. 14 (2). 293-313. doi:10.4208/eajam.2022-318.170723
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